Digital aerial images (DAI) include position, elevation and also spectral information (visible bands and near-infrared band) about
the captured area. The aim of this paper is to present the possibilities of automatic analysis of DAI for updating of the Fundamental
Base of Geographic Data of the Czech Republic with a focus on buildings. Regular updates of buildings (automatic detection of new
and demolished buildings) are based on the analysis of coloured point clouds created by an automatic image matching technique
from each time period. The created approach compares point clouds from different time periods to each other. The advantage of this
solution is that it is independent of the manner of keeping the buildings in the database. It does not matter whether the buildings
in the database have correct positions and their footprints correspond to the roof shapes or external walls. The involved method is
robust because a digital surface model generated by image matching techniques can contain numerous errors. Shaded areas
and objects with blurred textures are problematic for automatic image correlation algorithms and lead to false results. For this reason,
derived layers containing additional information are used. Shadow masks (layers with modelled shadows) are used
for the verification of indications and to filter out errors in the shaded areas using a contextual evaluation. Furthermore, additional
information about the road and railway networks and morphological operations of opening and closing were used to achieve more
accurate results. All these information sources are then evaluated using decision logic, which uses the generally applicable rules that
are available for different datasets without the need for modification. The method was tested on different datasets with various types
of buildings (villages, suburbs and city centres) which cover more than 20 square kilometres. The developed solution leads to very
promising results without the need of acquiring new data.